similar to: hist() and density

Hello, I have a problem with the hist() function and showing densities. The densities sum to 50 and not to 1! I use R version 2.9.1 (2009-06-26) and I load the seqinR library. My data is the following vector: [1] 0.1400000 0.2000000 0.2200000 0.2828283 0.1600000 0.1600000 0.3600000 [8] 0.1600000 0.2200000 0.2600000 0.2000000 0.3000000 0.2200000 0.2342342 [15] 0.1800000 0.2200000 0.1600000

Hello! Up to now I have been using hist() to display the distributions. Howevere, I noteiced strange numbers on y (vertical) axis, if I used probability = T or freq = F option. I thought it is a bug and launched the R-bug system and found some posts on that matter. Brian Ripley responded to one, that one should look at truehist() for that. Ok I can use truehist() if I want to see the ratios

Dear All, I am a undergraduate using R for the first time. It seems like an excellent program and one that I look forward to using a lot over the next few years, but I have hit a very basic problem that I can't solve. I want to produce a standardised histogram, i.e. one where the area under the graph is equal to 1. I look at the manual for the histogram function and find this: freq:

Hi, This is a very basic question, but I would like to undestand hist(). I thought that the hist( , freq=FALSE) should provide the relative frequencies (probabilities), and so they should sum 1, however: set.seed(2) ah <- hist(rnorm(100), freq=F) sum(ah$intensities) [1] 2 set.seed(2) bh <- hist(rlnorm(100), freq=F) sum(bh$intensities) [1] 0.4999996 I'm getting similar figures with

Hi, I am new to R...a recent convert from SAS. I have a dataset that looks like this: SEQ A1 A2 A 532.5 554.5 B 25.5 35.5 C 265.2 522.2 D 245.55 521.56 E 546.52 141.52 F 243.25 32.56 G 452.55 635.56 H 15.14 16.54 I 543.4 646.56 J 54.4 654.5 K 646.5 64.54 L 645.4 614.46 M 646.54 634.46 I want to make a histogram

Hello, To indicate probability densities instead of counts on a histogram, I specify freq = FALSE. However, I expect that summing all top y coordinates over all the intervals of the histogram will provide 1. 1) v <- c(0.2885, 0.2988, 0.3139, 0.2615, 0.3179, 0.3163, 0.2583, 0.3052, 0.2527, 0.3147, 0.3235, 0.2408, 0.2480, 0.3108, 0.3577, 0.2829, 0.2694, 0.3275, 0.3314, 0.2639, 0.3076,

hello, i am using the hist function with classified values. The class breaks are >1, so histogram$density is != 1. How to plot the histogram with freq=FALSE and the real class density values. I used: > h2 = hist(value, breaks = breaks_vector) > h2$density = round(h2$counts/sum(h2$counts), 2) > h2$intensities = h2$density > plot(h2, freq=F) but this isn't the best way, i

Hi, I have a couple of observations, a question or two, and perhaps a suggestion related to the plotting of density on the y-axis within the hist() function when freq=FALSE. I was using the function and trying to develop an intuitive understanding of what the density is telling me. After reading through this fairly helpful post:

Hi all, A friend send me a question on why does this: x<-rpois(100,1) sum( hist(x)$density ) Gives out "2" I tried this: sum( hist(x, freq =T)$density ) It didn't help. Then he came back with the following insight: # with breaks b<-c(0,0.9,1:8) sum(hist(x,breaks=b)$density) # Much more then 2 # but if we add weights according to the interval length

I have problems getting a histogram with relative frequencies on the y-axis. Here is an example data set: > a <- c(4.626, 4.627, 4.627, 4.628, 4.629, 4.629, 4.630, 4.631, 4.632, 4.632) > d = hist(a,freq=F) > d$density [1] 299.9999 100.0000 200.0000 100.0000 100.0000 200.0000 The obtained densities are given by counts/(total n * bin width), with bin width being

Dear list, I'm new to R, please bear with my silly questions. I'm trying to get an understanding of why the results I get from a call to hist() are not as I thought I would get. When I use the parameter freq=FALSE, I think the plot will contain bars that none of them is larger than 1, because they're probabilities. But for my code, the bars exceeded 1. The actual data seems

Dear R-Gurus, I wonder why 'density' values as shown in hist or plot(density(x)) are sometimes over 1. How can that be? Example >hist(rnorm(1000,sd=.5),freq=FALSE) The resulting plot shows density values below 1 on the y-axis. However, >hist(rnorm(1000,sd=.1),freq=FALSE) shows density values over 1. How to interpret density values over 1? Greetings, Johannes

Hi all, I'm trying to superimpose a rchisq density line over a histogram with something like: hist(alnlength) lines(density(rchisq(length(alnlength), 4)),col="red") But the rchisq line won't appear anywhere, Anyone knows what I am missing here? Thanks in advance, Albert.

In R0.61, In hist(), should the line rel.freqs <- counts/(sum(x) * diff(breaks)) computing the relative frequencies or height of the rectangles in a histogram not be rel.freqs <- counts/(sum(counts) * diff(breaks)) instead, or do I misunderstand something? Thanks, Philippe -- -------------------------------------------------------- Philippe Lambert Tel:

Hi, I don't understand what hist(x, freq=FALSE) does. At first I thought it would be just the relative frequencies instead of the absolute frequencies, by just computing "frequencies / n" in every category. But with a small dataset the y-values (densities) don't sum to one. Is there a way to get the histogram doing that? Or what is the idea of this density-computation?

Hello, all; I get an unexpected result when trying to plot a probability histogram with R1.9.1 on windows xp: #with the following code: > x <- runif(100,0,1) > hist(x) > hist(x, freq=F) > h <- hist(x, freq=F) > summary(h) # Length Class Mode #breaks 11 -none- numeric #counts 10 -none- numeric #intensities 10 -none- numeric #density 10

For the hist estimate >par(mex=1.3) >dens<-density(q) >options(scipen=4) > ylim<-range(dens$y) > h<-hist(q,breaks="scott",freq=FALSE,probability=TRUE, +? right=FALSE,xlim=c(9000,16000),ylim=ylim,main="Histogram of q(scott)") > lines(dens) >box() ? For the kernel estimate>options(scipen=4) > d <- density(q, bw =

Dear developers, the current implementation of hist.default() calculates 'density' (and 'intensities') as dens <- counts/(n*h) where h has been calculated before as h <- diff(fuzzybreaks) which results in 'fuzzy' values for the density, see e.g. > tmp <- hist(1:10,breaks=c(-2.5,2.5,7.5,12.5),plot=FALSE) > print(tmp$density,digits=15) [1]

Can someone please tell me to make a density histogram? hist makes one with count or relative frequency on the y-axis. I want the density, which is (rel freq)/(bin width) In the help I see: intensities: values f^(x[i]), as estimated density values. If `all(diff(breaks) == 1)', they are the relative frequencies `counts/n' and in general satisfy

Hi! Do not understand following behavior. > summary(test$dif) Min. 1st Qu. Median Mean 3rd Qu. Max. 0.7389 0.9713 0.9850 0.9818 1.0000 1.0000 length(test$dif) [1] 85879 tmp <- hist(test$dif,breaks=100,freq=FALSE) The density on the Y axis in the plot are in the range 0-200. Thought that the density should be in the range 0-1 (something like